Shoulder and Elbow Joint Angle Tracking With Inertial Sensors

Shoulder and Elbow Joint Angle Tracking With Inertial Sensors
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DOI:
10.1109/tbme.2012.2208750
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发表时间:
2012-09-01
影响因子:
4.6
通讯作者:
McNames, James
McNames, James
中科院分区:
工程技术2区
文献类型:
--
作者:
El-Gohary, Mahmoud;McNames, James

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可穿戴惯性系统最近被用来跟踪实验室内外的人体运动。持续监测人体运动可以提供与个人身体活动水平和功能能力相关的有价值的信息。传统上,方向是通过积分陀螺仪的角速度来计算的。然而,测量速度的微小漂移会导致积分误差随着时间的推移而增加。为了补偿这种漂移,通常使用卡尔曼或扩展卡尔曼滤波器将来自加速度计的补充数据融合到跟踪系统中。在这项研究中,我们将用于控制机器人手臂的运动学模型与状态空间方法相结合,使用两个可穿戴惯性测量单元连续估计人类肩膀和肘部的角度。我们使用无迹卡尔曼滤波器来实现非线性状态空间惯性跟踪器。将使用我们的惯性跟踪器从 8 名受试者获得的肩关节和肘关节角度与从光学跟踪参考系统获得的角度进行比较。平均而言,所有肩部和肘部角度的 RMS 角度误差均小于 8 度。所有受试者所有运动任务的平均相关系数为 r >= 0.95。我们的惯性跟踪器和光学参考系统之间的一致性是针对手臂的常规和快速运动而获得的。可以使用相同的方法来跟踪其他关节的运动。
Wearable inertial systems have recently been used to track human movement in and outside of the laboratory. Continuous monitoring of human movement can provide valuable information relevant to individuals' level of physical activity and functional ability. Traditionally, orientation has been calculated by integrating the angular velocity from gyroscopes. However, a small drift in the measured velocity leads to increasing integration error over time. To compensate that drift, complementary data from accelerometers are normally fused into tracking systems using the Kalman or extended Kalman filter. In this study, we combine kinematic models designed for control of robotic arms with state-space methods to continuously estimate the angles of human shoulder and elbow using two wearable inertial measurement units. We use the unscented Kalman filter to implement the nonlinear state-space inertial tracker. Shoulder and elbow joint angles obtained from 8 subjects using our inertial tracker were compared to the angles obtained from an optical-tracking reference system. On average, there was an RMS angle error of less than 8 degrees for all shoulder and elbow angles. The average correlation coefficient for all movement tasks among all subjects was r >= 0.95. This agreement between our inertial tracker and the optical reference system was obtained for both regular and fast-speed movement of the arm. The same method can be used to track movement of other joints.